CN112963145A - Method for predicting gas well productivity of carbonate reservoir - Google Patents
Method for predicting gas well productivity of carbonate reservoir Download PDFInfo
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Abstract
The invention discloses a method for predicting the productivity of a gas well of a carbonate reservoir, which can rapidly predict the productivity of the gas well based on static data of a well to be predicted and comprises the following steps: firstly, collecting logging parameters of a main power layer developed by a gas well with a drilled carbonate reservoir and single-test productivity of the layer; respectively intersecting the productivity and each logging parameter by using a chart intersection method, analyzing logging response characteristics corresponding to different productivities according to intersection results, and determining the correlation between the gas well productivity and each logging parameter by using a fitting curve correlation coefficient R; and selecting logging parameters with strong correlation to calculate the well productivity prediction factor F, fitting a correlation relational expression between the productivity of the unit gas wells with different karst ancient landforms and the productivity prediction factor by using a plurality of gas well sample points, and rapidly predicting the productivity of the well to be tested by using the relational expression. The invention combines the karst ancient landform with the gas well productivity prediction factor to predict the productivity, and the productivity coincidence rate is obviously improved.
Description
Technical Field
The application relates to the technical field of carbonate gas well development, in particular to a method for predicting the productivity of a carbonate reservoir gas well.
Background
The method belongs to a method for obtaining the capacity by using dynamic data, and has the advantages that the capacity is obtained accurately, and the defects that the capacity can be obtained only after the stratum test is passed are overcome. However, the field productivity building site urgently needs to predict the productivity of the gas well quickly through static data before formation testing or under the condition of no testing. The significance of rapidly predicting energy production prior to formation testing is: the gas testing sequence is optimized. The high-yield gas well can be predicted to be arranged to test in advance and put into production in advance, and the production pressure is relieved; and secondly, the testing horizon is optimized, and the well construction cost is saved. If the gas well is predicted to have no production capacity, the sulfur-proof casing pipe is not required to be put down, so that the cost is saved; if the predicted reservoir productivity is low, a plurality of small laminated layers can be tested; if the high yield of the reservoir is predicted, the layer can be tested singly, and the testing effect is improved. The significance of fast prediction of energy production when the formation is not tested is: saving the development cost of the gas field; and secondly, the gas well is reasonably produced and rapidly put into operation.
At present, the domestic method for rapidly predicting the productivity of a carbonate reservoir gas well based on static data mainly predicts the productivity by establishing the correlation between the physical property and the gas content of the reservoir and the productivity of the gas well, such as: [ Liuhai. 2004] carbonate reservoir productivity prediction method exploration, and the establishment of a productivity prediction evaluation chart is proposed to predict the productivity; [ Wangbuiqing.2014 ] based on a remote detection acoustic carbonate reservoir productivity prediction technology, the semi-quantitative prediction of carbonate reservoir productivity is carried out by utilizing the energy of reflected waves; [ Huiwei.2014 ] deep carbonate rock gas layer productivity prediction, and the capacity is predicted by utilizing invasion depth and influence of clay minerals on reservoir sensitivity; the method is suitable for predicting the productivity of the pore type carbonate reservoir based on the combination of conventional logging and microresistivity scanning imaging logging information; [ Lining.2015 ] applies CT analysis and nuclear magnetic logging to predict the gas production of carbonate rock, and proposes a new method for predicting the gas production of a carbonate rock reservoir by utilizing CT70 porosity. The methods have long data acquisition time and are difficult to quickly predict the productivity of the gas well, and the accuracy of the prediction result is low although the productivity can be quickly predicted by only depending on a plate method.
Disclosure of Invention
The application provides a method for predicting gas well productivity of a carbonate reservoir, which aims to solve the problems that the gas well productivity prediction method in the prior art is long in data acquisition time and difficult to rapidly predict gas well productivity, and the productivity can be rapidly predicted by only depending on a graphic method, but the accuracy of a prediction result is low.
The technical scheme adopted by the application is as follows:
the method for predicting the productivity of the gas well of the carbonate reservoir comprises the following steps:
collecting logging parameters of a drilled carbonate reservoir gas well development main stratum and single-test productivity of the stratum;
respectively intersecting the productivity and each logging parameter by using a chart intersection method;
analyzing logging response characteristics corresponding to different productivity of the gas well according to the rendezvous result, and quantifying the relation between the productivity of the gas well and the logging parameters;
determining the correlation between the gas well productivity and each logging parameter according to the response characteristics and the relationship between the gas well productivity and each logging parameter;
selecting a set number of the logging parameters with strong correlation according to actual requirements, and calculating productivity prediction factors of the gas well;
determining three-level karst ancient landform units where the gas wells are located, and classifying the gas wells according to different landform units;
establishing a correlation relational expression between the productivity of the unit gas wells with different landforms and the corresponding productivity prediction factors;
and predicting the gas well productivity of different landform units through the correlation relational expression.
Preferably, the logging parameters include resistivity measured and calculated by a logging instrument, compensated neutrons, density of a gas reservoir, acoustic moveout, porosity, permeability, gas saturation and effective thickness. .
Preferably, the respectively crossing the productivity and the logging parameters by using a plate crossing method comprises:
and respectively intersecting the productivity of the gas well with each logging parameter by using a chart intersection method to obtain the upper limit value and the lower limit value of each logging parameter corresponding to different productivities.
Preferably, the determining the correlation between the gas well productivity and each logging parameter according to the response characteristics and the relationship between the gas well productivity and each logging parameter comprises:
according to the response characteristics and the data of the gas well productivity and each logging parameter, establishing a correlation fitting curve of the gas well productivity and each logging parameter;
and determining the correlation between the gas well productivity and each logging parameter by using a correlation coefficient R generated by the correlation fitting curve.
Preferably, the correlation coefficient R value generated by fitting a curve to the correlation between the gas well productivity and each logging parameter is closer to 1, which means that the correlation is more close, and closer to 0, which means that the correlation is worse.
Preferably, the selecting a set number of the logging parameters with strong correlation according to actual demands and calculating productivity prediction factors of the gas well comprise:
setting and selecting the logging parameters with strong correlation as K, Ac and POR according to actual requirements, and comprehensively evaluating to obtain a productivity prediction factor calculation formula of the gas well as:
F＝K×(Ac-Aclower limit value)×POR
Wherein K is permeability, Ac is sonic time difference, AcLower limit valuePOR is the porosity, the lower limit of the acoustic moveout.
Preferably, the establishing of the correlation relation between the productivity of the unit gas wells with different landforms and the corresponding productivity prediction factors comprises the following steps:
establishing a fitting curve between the productivity of the unit gas wells with different landforms and the corresponding productivity prediction factors through an EXCEL chart;
and selecting a polynomial according to a fitting curve between the productivity and the corresponding productivity prediction factors and a function expression of the fitting curve to obtain a function expression of the fitting curve, namely a correlation relation between the productivity of the unit gas wells with different landforms and the corresponding productivity prediction factors.
Preferably, the predicting the productivity of the gas wells of different landform units through correlation relations between the productivity and corresponding prediction factors comprises the following steps:
substituting the prediction factors of the gas well productivity into the correlation relational expression between the productivity of the corresponding geomorphic unit and the corresponding prediction factors, and calculating the unimpeded flow of the gas well, namely obtaining the predicted productivity value of the gas well.
The technical scheme of the application has the following beneficial effects:
the productivity prediction method is based on static data such as well logging, through plate intersection and curve fitting, well unobstructed flow logging response characteristics of the gas well are analyzed, the correlation between the gas well productivity and logging parameters is determined, and the gas well productivity prediction factor correlation relational expression on different karst ancient landform units is obtained by using the reservoir productivity prediction factors, so that the gas well productivity is rapidly predicted. The gas well stratum test sequence is optimized, the gas well production allocation is reasonable, the production rate of the gas well is accelerated, the production pressure of the gas field is relieved, the well construction cost is saved, and the test effect is improved.
Drawings
In order to more clearly explain the technical solution of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method for predicting the productivity of a gas well in a carbonate reservoir according to the present application;
FIG. 2 is a cross-plot of MAFI 4 single-test no-resistance flow versus well log interpretation porosity, permeability response in this application;
FIG. 3 is a schematic diagram of a Mawu 4 single-test non-resistance flow and acoustic time difference response fitting curve in the present application;
fig. 4 is a schematic view of a fitting curve of the masu 4 single-test non-resistance flow and the reservoir productivity prediction factor in the present application.
Detailed Description
Reference will now be made in detail to embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following examples do not represent all embodiments consistent with the present application. But merely as exemplifications of systems and methods consistent with certain aspects of the application, as recited in the claims.
Referring to fig. 1, a flow chart of a method for predicting the productivity of a gas well in a carbonate reservoir is shown.
The method for predicting the productivity of the gas well of the carbonate reservoir comprises the following steps:
collecting logging parameters of a drilled carbonate reservoir gas well development main stratum and single-test productivity of the stratum;
respectively intersecting the productivity and each logging parameter by using a chart intersection method;
analyzing logging response characteristics corresponding to different productivity of the gas well according to the rendezvous result, and quantifying the relation between the productivity of the gas well and the logging parameters;
determining the correlation between the gas well productivity and each logging parameter according to the response characteristics and the relationship between the gas well productivity and each logging parameter;
selecting a set number of the logging parameters with strong correlation according to actual requirements, and calculating productivity prediction factors of the gas well;
determining three-level karst ancient landform units where the gas wells are located, and classifying the gas wells according to different landform units;
establishing a correlation relational expression between the productivity of the unit gas wells with different landforms and the corresponding productivity prediction factors;
and predicting the gas well productivity of different landform units through the correlation relational expression.
The productivity prediction method comprises the steps of firstly, obtaining various geological parameters such as porosity, permeability, gas saturation and effective thickness of a gas well development main stratum by using logging, analyzing gas well gas testing unobstructed flow and logging response characteristics by a multi-parameter intersection method and a curve fitting method, quantifying the relation between gas well productivity and logging parameters, determining the correlation between gas well productivity and logging parameters, introducing reservoir productivity prediction factors, and obtaining correlation relational expressions of gas well productivity and reservoir productivity prediction factors of different karst ancient geomorphic units, so that the gas well productivity is rapidly predicted.
The logging parameters comprise resistivity, compensated neutrons, density of a gas storage layer, acoustic time difference, porosity, permeability, gas saturation and effective thickness measured and calculated by a logging instrument.
The respectively intersecting the productivity and the logging parameters by using a chart intersection method comprises the following steps:
and respectively intersecting the productivity of the gas well with each logging parameter by using a chart intersection method to obtain the upper limit value and the lower limit value of each logging parameter corresponding to different productivities.
Determining the correlation between the gas well productivity and each logging parameter according to the response characteristics and the relationship between the gas well productivity and each logging parameter, wherein the correlation comprises the following steps:
according to the response characteristics and the data of the gas well productivity and each logging parameter, establishing a correlation fitting curve of the gas well productivity and each logging parameter;
and determining the correlation between the gas well productivity and each logging parameter by using a correlation coefficient R generated by the correlation fitting curve.
And the closer to 1, the closer to 0, the closer to the correlation coefficient R value generated by the correlation fitting curve of the gas well productivity and each logging parameter, the closer to 1, the closer to 0, the closer to the correlation coefficient R value is represented by the worse correlation coefficient R value.
The method for calculating the productivity prediction factor of the gas well by selecting the logging parameters with strong correlation in set quantity according to actual requirements comprises the following steps:
setting and selecting the logging parameters with strong correlation as K, Ac and POR according to actual requirements, and comprehensively evaluating to obtain a productivity prediction factor calculation formula of the gas well as:
F＝K×(Ac-Aclower limit value)×POR
Wherein K is permeability, Ac is sonic time difference, AcLower limit valuePOR is the porosity, the lower limit of the acoustic moveout.
The productivity prediction factor is obtained by considering the comprehensive influence of a plurality of logging parameters on the gas well productivity and comprehensively evaluating the selected logging parameters with strong correlation, and other comprehensive evaluation methods and productivity prediction factor calculation formulas can also be adopted.
The establishing of the correlation relational expression between the productivity of the unit gas wells with different landforms and the corresponding productivity prediction factors comprises the following steps:
establishing a fitting curve between the productivity of the unit gas wells with different landforms and the corresponding productivity prediction factors through an EXCEL chart;
and selecting a polynomial according to a fitting curve between the productivity and the corresponding productivity prediction factors and a function expression of the fitting curve to obtain a function expression of the fitting curve, namely a correlation relation between the productivity of the unit gas wells with different landforms and the corresponding productivity prediction factors.
Predicting the gas well productivity of different landform units according to the correlation relational expression between the productivity and the corresponding prediction factors, wherein the predicting comprises the following steps:
substituting the prediction factors of the gas well productivity into the correlation relational expression between the productivity of the corresponding geomorphic unit and the corresponding prediction factors, and calculating the unimpeded flow of the gas well, namely obtaining the predicted productivity value of the gas well.
Example one
For example, the main force reservoir of the Su X well in the underground ancient world of the Ordos basin is Mawu 4, the method comprises the steps of firstly utilizing a plate intersection method, comparing multiple parameters, intersecting each parameter obtained by logging with a single-test non-resistance flow of the layer, wherein the single-test non-resistance flow is the productivity of a gas well, analyzing the logging response characteristics of a high-yield well with the non-resistance flow of more than 20 ten thousand squares/day and a low-yield well with the non-resistance flow of less than 4 ten thousand squares/day, and quantifying the relation between the productivity and each logging parameter, and is shown in a table 1 and a figure 2:
TABLE 1 Eldos basin horse five4Gas-testing non-resistance flow and logging response characteristic data table
And then, by establishing a fitting curve of correlation between the gas test unobstructed flow and the logging parameters of the main bearing stratum section for developing the lower ancient gas reservoir, solving a correlation coefficient R value, and analyzing the correlation between the gas well productivity and the logging parameters, as shown in the following table 2 and figure 3, the fitting curve shows that the correlation between the productivity and the permeability, the acoustic wave time difference and the porosity of the main bearing stratum horse five 4 for developing the Ordos basin gas well is better.
TABLE 2 Eldos basin horse five4Gas-testing non-resistance flow and logging parameter related coefficient table
Predicting the gas well productivity by using the reservoir productivity prediction factor: and establishing a productivity prediction factor correlation relation between the productivity of the unit gas wells with different ancient landforms and the selected logging parameters with strong correlation through the intersection graph and the fitting curve.
Reservoir productivity prediction factor: in this embodiment, the logging parameters K, Ac, and POR with strong correlation are selected, and the productivity prediction factor calculation formula of the gas well obtained through comprehensive evaluation is as follows:
F＝K×(Ac-Aclower limit value)×POR
Wherein K is permeability, Ac is sonic time difference, AcLower limit valuePOR is the porosity, the lower limit of the acoustic moveout.
Selecting a horse five 4 reservoir single-layer test well in a research area, calculating a reservoir capacity prediction factor of each well, and classifying according to a landform unit where a gas well is located, so as to establish a horse five 4 single-test unimpeded flow and reservoir capacity prediction factor fitting curve, and obtain a correlation formula of the unimpeded flow and the reservoir capacity prediction factor, as shown in table 3 and figure 4:
TABLE 3 Eardos basin underground ancient horse five4Parameter table related to unimpeded flow and reservoir productivity prediction factors of different karst ancient landforms
And (3) rapidly predicting the gas well productivity by using a correlation formula: the SuXwell is positioned at the position of a karst ancient slope, the reservoir productivity prediction factor F is calculated to be 38.9 by utilizing logging interpretation static parameter values (K, Ac and POR), and then the correlation formula of the ancient slope unit gas well productivity and the reservoir productivity prediction factor is utilized: y-0.0444 x2+4.488x-2.1088, the productivity prediction factor F ═ x ═ 2.108838.9 is substituted into the correlation formula to calculate the well unimpeded flow rate y which is 105.28 multiplied by 104m3D, the actual gas testing and production-seeking unimpeded flow is 115 multiplied by 104m3The error is 8.0 percent.
And assuming that the three-level karst ancient landform units in the region are ancient hillocks, ancient slopes, ancient swales, ancient grooves and the like. The karst ancient landform has a main control function on the reservoir formation, and a slope zone between an ancient dune and an ancient groove at a relatively high part of the karst ancient landform is a favorable gas-containing part and is often a main distribution area of the gas testing high-yield well; the ancient depression and the groove at the relatively low part are leaching dissolved substance collecting places, so that the reservoir is compact and is often a low-yield or non-yield area. The method is applied to ancient gas reservoir development under the Hull-Doss basin Jing-edge gas field and the Su-Li Ge gas field, and compared with the yield obtaining result of a gas testing well, the method saves the production time of a single well for 16 days, improves the coincidence rate by more than 20% compared with the prior method only applying a rendezvous chart method, and greatly improves the productivity prediction accuracy rate.
The productivity prediction method is based on static data such as well logging, through plate intersection and curve fitting, well unobstructed flow logging response characteristics of the gas well are analyzed, the correlation between the gas well productivity and logging parameters is determined, and the gas well productivity prediction factor correlation relational expression on different karst ancient landform units is obtained by using the reservoir productivity prediction factors, so that the gas well productivity is rapidly predicted. The gas well stratum test sequence is optimized, the gas well production allocation is reasonable, the production rate of the gas well is accelerated, the production pressure of the gas field is relieved, the well construction cost is saved, and the test effect is improved.
The embodiments provided in the present application are only a few examples of the general concept of the present application, and do not limit the scope of the present application. Any other embodiments extended according to the scheme of the present application without inventive efforts will be within the scope of protection of the present application for a person skilled in the art.
Claims (8)
1. The method for predicting the productivity of the gas well in the carbonate reservoir is characterized by comprising the following steps of:
collecting logging parameters of a drilled carbonate reservoir gas well development main stratum and single-test productivity of the stratum;
respectively intersecting the productivity and each logging parameter by using a chart intersection method;
analyzing logging response characteristics corresponding to different productivity of the gas well according to the rendezvous result, and quantifying the relation between the productivity of the gas well and the logging parameters;
determining the correlation between the gas well productivity and each logging parameter according to the response characteristics and the relationship between the gas well productivity and each logging parameter;
selecting a set number of the logging parameters with strong correlation according to actual requirements, and calculating productivity prediction factors of the gas well;
determining three-level karst ancient landform units where the gas wells are located, and classifying the gas wells according to different landform units;
establishing a correlation relational expression between the productivity of the unit gas wells with different landforms and the corresponding productivity prediction factors;
and predicting the gas well productivity of different landform units through the correlation relational expression.
2. The method for predicting the productivity of a gas well in a carbonate reservoir according to claim 1, wherein the logging parameters comprise resistivity, compensated neutrons, density of a gas storage layer, acoustic moveout, porosity, permeability, gas saturation and effective thickness measured and calculated by a logging instrument.
3. The method for predicting the productivity of the gas well in the carbonate reservoir as claimed in claim 2, wherein the step of respectively meeting the productivity and the logging parameters by using a plate-crossing method comprises the following steps:
and respectively intersecting the productivity of the gas well with each logging parameter by using a chart intersection method to obtain the upper limit value and the lower limit value of each logging parameter corresponding to different productivities.
4. The method for predicting the productivity of a carbonate reservoir gas well as claimed in claim 3, wherein the step of determining the correlation between the productivity of the gas well and each logging parameter according to the response characteristics and the relationship between the productivity of the gas well and each logging parameter comprises the following steps:
according to the response characteristics and the data of the gas well productivity and each logging parameter, establishing a correlation fitting curve of the gas well productivity and each logging parameter;
and determining the correlation between the gas well productivity and each logging parameter by using a correlation coefficient R generated by the correlation fitting curve.
5. The method for predicting the productivity of a carbonate reservoir gas well as claimed in claim 4, wherein the closer to 1 the correlation coefficient R value generated by the curve fit of the correlation between the productivity of the gas well and each logging parameter is, the more close the correlation is represented by 1, and the closer to 0 the correlation is represented by poor correlation.
6. The method for predicting the productivity of the gas well in the carbonate reservoir according to claim 5, wherein the step of selecting a set number of the logging parameters with strong correlation according to actual demands and calculating the productivity prediction factor of the gas well comprises the following steps:
setting and selecting the logging parameters with strong correlation as K, Ac and POR according to actual requirements, and comprehensively evaluating to obtain a productivity prediction factor calculation formula of the gas well as:
F＝K×(Ac-Aclower limit value)×POR
Wherein K is permeability, Ac is sonic time difference, AcLower limit valuePOR is the porosity, the lower limit of the acoustic moveout.
7. The method for predicting the productivity of a carbonate reservoir gas well as claimed in claim 6, wherein the step of establishing a correlation between the productivity of unit gas wells with different landforms and the corresponding productivity prediction factors comprises the following steps:
establishing a fitting curve between the productivity of the unit gas wells with different landforms and the corresponding productivity prediction factors through an EXCEL chart;
and selecting a polynomial according to a fitting curve between the productivity and the corresponding productivity prediction factors and a function expression of the fitting curve to obtain a function expression of the fitting curve, namely a correlation relation between the productivity of the unit gas wells with different landforms and the corresponding productivity prediction factors.
8. The method for predicting the productivity of the gas well of the carbonate reservoir according to claim 7, wherein the predicting the productivity of the gas well of different landform units through the correlation relation between the productivity and the corresponding prediction factors comprises the following steps:
substituting the prediction factors of the gas well productivity into the correlation relational expression between the productivity of the corresponding geomorphic unit and the corresponding prediction factors, and calculating the unimpeded flow of the gas well, namely obtaining the predicted productivity value of the gas well.
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